TY - JOUR
T1 - Artificial intelligence and imaging
T2 - Opportunities in cardio-oncology
AU - Madan, Nidhi
AU - Lucas, Julliette
AU - Akhter, Nausheen
AU - Collier, Patrick
AU - Cheng, Feixiong
AU - Guha, Avirup
AU - Zhang, Lili
AU - Sharma, Abhinav
AU - Hamid, Abdulaziz
AU - Ndiokho, Imeh
AU - Wen, Ethan
AU - Garster, Noelle C.
AU - Scherrer-Crosbie, Marielle
AU - Brown, Sherry Ann
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/3
Y1 - 2022/3
N2 - Cardiovascular disease is a leading cause of death in cancer survivors. It is critical to apply new predictive and early diagnostic methods in this population, as this can potentially inform cardiovascular treatment and surveillance decision-making. We discuss the application of artificial intelligence (AI) technologies to cardiovascular imaging in cardio-oncology, with a particular emphasis on prevention and targeted treatment of a variety of cardiovascular conditions in cancer patients. Recently, the use of AI-augmented cardiac imaging in cardio-oncology is gaining traction. A large proportion of cardio-oncology patients are screened and followed using left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), currently obtained using echocardiography. This use will continue to increase with new cardiotoxic cancer treatments. AI is being tested to increase precision, throughput, and accuracy of LVEF and GLS, guide point-of-care image acquisition, and integrate imaging and clinical data to optimize the prediction and detection of cardiac dysfunction. The application of AI to cardiovascular magnetic resonance imaging (CMR), computed tomography (CT; especially coronary artery calcium or CAC scans), single proton emission computed tomography (SPECT) and positron emission tomography (PET) imaging acquisition is also in early stages of analysis for prediction and assessment of cardiac tumors and cardiovascular adverse events in patients treated for childhood or adult cancer. The opportunities for application of AI in cardio-oncology imaging are promising, and if availed, will improve clinical practice and benefit patient care.
AB - Cardiovascular disease is a leading cause of death in cancer survivors. It is critical to apply new predictive and early diagnostic methods in this population, as this can potentially inform cardiovascular treatment and surveillance decision-making. We discuss the application of artificial intelligence (AI) technologies to cardiovascular imaging in cardio-oncology, with a particular emphasis on prevention and targeted treatment of a variety of cardiovascular conditions in cancer patients. Recently, the use of AI-augmented cardiac imaging in cardio-oncology is gaining traction. A large proportion of cardio-oncology patients are screened and followed using left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), currently obtained using echocardiography. This use will continue to increase with new cardiotoxic cancer treatments. AI is being tested to increase precision, throughput, and accuracy of LVEF and GLS, guide point-of-care image acquisition, and integrate imaging and clinical data to optimize the prediction and detection of cardiac dysfunction. The application of AI to cardiovascular magnetic resonance imaging (CMR), computed tomography (CT; especially coronary artery calcium or CAC scans), single proton emission computed tomography (SPECT) and positron emission tomography (PET) imaging acquisition is also in early stages of analysis for prediction and assessment of cardiac tumors and cardiovascular adverse events in patients treated for childhood or adult cancer. The opportunities for application of AI in cardio-oncology imaging are promising, and if availed, will improve clinical practice and benefit patient care.
KW - Artificial intelligence
KW - Cancer
KW - Cardiac tumors
KW - Cardio-oncology
KW - Echocardiography
KW - Imaging
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U2 - 10.1016/j.ahjo.2022.100126
DO - 10.1016/j.ahjo.2022.100126
M3 - Article
AN - SCOPUS:85134366659
SN - 2666-6022
VL - 15
JO - American Heart Journal Plus: Cardiology Research and Practice
JF - American Heart Journal Plus: Cardiology Research and Practice
M1 - 100126
ER -